Abstract
The kernel method was originally invented in Aizerman et al. (Autom. Remote Control, 25, 821\textendash{}837, 1964). The key idea is to project the training set in a lower-dimensional space into a high-dimensional kernel (feature) space by means of a set of nonlinear kernel functions.
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APA
Du, K.-L., & Swamy, M. N. S. (2014). Other Kernel Methods. In Neural Networks and Statistical Learning (pp. 525–545). Springer London. https://doi.org/10.1007/978-1-4471-5571-3_17
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